
from fastapi import APIRouter, Request
from fastapi.templating import Jinja2Templates
from fastapi.responses import JSONResponse

pie_data = APIRouter()

# # 加载并分析数据
# import pandas as pd
#
# df1 = pd.read_excel("/Users/xialubanzhuan/Desktop/fastapi/api/附件1_副本.xlsx")
# # df2 = pd.read_excel("/Users/xialubanzhuan/Desktop/fastapi/api/附件2_副本.xlsx")
# df3 = pd.read_excel("/Users/xialubanzhuan/Desktop/fastapi/api/附件3_副本.xlsx")
#
# df3['日期'] = pd.to_datetime(df3['日期'])
# df3['月份'] = df3['日期'].dt.month
#
# df=pd.merge(df3, df1[["单品编码","单品名称"]], on="单品编码")
# print(df.head(5))
#
# grouped = df.groupby('单品名称')
# print(grouped)
#
# result = {}
# for name, group in grouped:
#     print(name)
#     print(group)
#     unique_months = group['月份'].unique()
#     total_months = len(unique_months)
#     season = []
#     season_list = [0]*4
#     if 3 in unique_months or 4 in unique_months or 5 in unique_months:
#         season.append(" 春季")
#         season_list[0] = 1
#     if 6 in unique_months or 7 in unique_months or 8 in unique_months:
#         season.append(" 夏季")
#         season_list[1] = 1
#     if 9 in unique_months or 10 in unique_months or 11 in unique_months:
#         season.append(" 秋季")
#         season_list[2] = 1
#     if 12 in unique_months or 1 in unique_months or 2 in unique_months:
#         season.append(" 冬季")
#         season_list[3] = 1
#     result[name] = {
#         '出现的月份': unique_months,
#         '总共出现的月份数': total_months,
#         '出现的季节': season,
#         "季节数": len(season),
#         "季节列表": season_list
#     }
#
# count_all = 0
# count_all_list = []
# for key, value in result.items():
#     if value['季节数'] == 4:
#         count_all += 1
#         count_all_list.append(key)
# # print(f" 单品编码 {key} 出现在以下月份: {', '.join(map(str, value['出现的月份']))}，总出现的月份数: {value['总共出现的月份数']}, 出现在 {value['出现的季节']}")
# print(count_all)
# print(count_all_list) ############ 常年可供应的蔬菜和水果 时令蔬菜和水果 统计 #############
# df['年份'] = df['日期'].dt.year
# result = df.groupby(['单品编码', '年份']).agg({'日期': 'nunique'}).reset_index()
# result.rename(columns={'日期': '天数'}, inplace=True)
#
# #print(result)
# max_days = result.groupby('单品编码')['天数'].max().reset_index()
# # print(max_days)
#
# filtered_df = max_days[max_days['天数'] <= 15]
# cnt = 0
# cnt_list = []
# for index, row in filtered_df.iterrows():
#     cnt_list.append(row['单品编码'])
#     print(f" 单品编码：{row['单品编码']}，一年最多出现{row['天数']}天")
#     cnt += 1
# print(cnt)


data_pie=[{'name':'常年性','value':112},
    {'name':'时令性','value':69},
          {'name':'季节性','value':70}]




@pie_data.get("/getdata")
async def get_data_0():

    result = data_pie

    return JSONResponse(result)